Overview
The role of AI Engineer involves working on the development of production-level agentic AI systems in a regulated, customer-facing environment. The successful candidate will design and implement AI-powered features while collaborating with a team and integrating various technologies to enhance AI workflows.
Responsibilities
- Design, build, and ship AI-powered features for agentic systems.
- Integrate commercial and open-source LLMs into workflows.
- Implement agent and orchestration frameworks such as LangChain and Semantic Kernel.
- Conduct model-level work using PyTorch and the Hugging Face ecosystem.
- Establish strong schema, validation, and state management practices with tools like Pydantic and Zod.
- Collaborate in a team environment to meet project deadlines and objectives.
- Participate in knowledge sharing and learning opportunities within the team.
Requirements
- Proficiency in programming languages such as Python, Go, and TypeScript.
- Experience with cloud services, particularly AWS and/or GCP.
- Familiarity with container orchestration tools like Kubernetes.
- Knowledge of distributed systems and event-driven architectures, including Kafka.
- Experience with orchestration frameworks like LangGraph or AirFlow.
- Strong background in working with the Hugging Face ecosystem for AI models.
- Ability to implement schema and validation techniques effectively.